The opportunity to approach an organisation, which is dependent on Physi- cal Asset Management (PAM) for their financial success, presented itself as a case study. A mining organisation in South Africa was invited to take part in the case study and substantiation of the QIIPMR methodology. Due to a non-disclosure agreement, no further details of the mining organisation can be provided. However, some generic information on the mining operation, whose data is used in this case study, is provided to better conceptualise the origin
of the KPI data.
The KPI data is collected from one of the mining organisation’s open-pit, thermal coal mines. The particular mine is chosen as it has different organi- sational silos at site, but most importantly, it manages the entire mining and delivery process (to a single client) of thermal coal. This study can therefore use KPI data from a single business entity solely responsible for the afore- mentioned process. It allows for a variety of performance data to be assessed, as well as ensuring Performance Measurement (PM) and Performance Man- agement (PMa) standards are maintained throughout all organisational silos. Furthermore, a single PMS is employed to measure and monitor the perfor- mance of the mine, eliminating the need to merge different KPI databases and to account for different KPI standards.
The mine is an engineering intensive operation with on-site workshop fa- cilities used to service and maintain their multiple fleets of physical assets. In addition, the productivity and profitability of the mine is greatly dependent on some critical physical assets, such as draglines, shovels and haulers. Therefore, the majority of the mine’s overall PM efforts are focused on the productivity and production-availability of their important physical assets. This presents an opportunity to identify the possible relationships that may exist between the KPIs focused on physical asset productivity and production-availability, and the KPIs focused on measuring the mine’s financial performance.
The following sections detail the elements and characteristics of the case study. First, the objectives and delimitations of the case study are provided. The specific phases of QIIPMR and QRPMS which are to be completed in this case study are also stated. The assumptions made in the case study are stated where required to improve the understanding and completion of the neces- sary processes. Finally, the tasks required to deliver the data for QIIPMR’s substantiation are executed, and a discussion on the results is provided.
4.2.1
Case Study Objectives And Delimitations
The case study is effectively completed by remaining within its scope, and by executing its sequential objectives. The objectives of this case study are given in Table 4.1.
The delimitations of the case study are defined along with those of the study in Section 1.4. For convenience, the delimitations are repeated below.
• The case study will only employ KPI data from a single thermal coal mine in South Africa.
Table 4.1: Case study objectives
Obj. # Research objective
1. Identify a suitable source of KPI data. The data source must comply with the PMS criteria (detailed in Section 3.3.1.1) of both QRPMS and
QIIPMR.
2. Collect, filter and approve the KPI data as required by both QRPMS and QIIPMR. The data treatment process is detailed in Section 3.3.1.2. 3. Complete PCA and compute the PCs of the KPI dataset.
4. Select the number of PCs for further analysis using the K1, PA and scree plot criterion.
5. Complete a discussion of the results obtained from PCA and the selection criteria.
6. Assess and substantiate the QIIPMR methodology.
• The case study will only focus on the substantiation of the alterations made to the QRPMS methodology; a complete iteration of the QIIPMR methodology will not be carried out (expanded on in Section 4.2.2) This concludes the statement of the objectives and delimitations of the case study completed in this chapter. The following section discusses the appropriate QRPMS and QIIPMR constituents which need to be completed for the QIIPMR methodology to be substantiated.
4.2.2
QIIPMR And QRPMS Constituent Selection For
Execution
The assessment and substantiation of the newly developed QIIPMR methodol- ogy follows. This requires a comparison of QIIPMR’s results and deliverables with that of the QRPMS methodology. QIIPMR employs QRPMS as a founda- tional framework and therefore many of the QRPMS constituents are adopted unaltered into the QIIPMR methodology. QIIPMR and QRPMS share the same four executable phases; phases which are described in Section 3.3 and Section 3.5.
The phases shared between QIIPMR and QRPMS are similar in all as- pects, apart from the third phase. The selection criteria employed by QRPMS and QIIPMR differ when determining which PCs to retain for further analy- sis. QRPMS employs the Guttman-Kaiser criterion (K1), whereas QIIPMR employs both the Parallel Analysis (PA) criterion and the scree plot. In order to simplify the referencing of these shared phases for the remainder of the case study, they will be referred to as Phases 1 to 4 from henceforth. Furthermore, the focus of differentiating between QRPMS’s Phase 3 and QIIPMR’s Phase
3 will be placed on the different selection criteria employed.
Phase 3 involves the completion of PCA and PLS for the identification and quantification of inter-KPI relationships, respectively. PCA must be completed to compute the PCs (of the KPI dataset) required to execute the three selection criteria to substantiate QIIPMR. However, the quantification of the selected PCs (through the execution of PLS) is deemed redundant for the requirements of this study for the following reasons:
• The quantification of the PCs retained for further analysis does not con- tribute justifiable and relevant information for the assessment and sub- stantiation of the QIIPMR methodology.
• The quantification of KPI relationships using the PLS technique has been successfully completed by Rodriguez et al. (2009) and Patel et al. (2008). Therefore, it is not required to prove or demonstrate this quantification method.
The above shows that only Phase 1 and Phase 2 are required to be com- pleted in full, whereas Phase 3 can be partially completed as it is not re- quired to perform PLS for the assessment and substantiation of the QIIPMR methodology. The identification of the Business Driver Key Performance Indi- cators (BDKPIs) (using both QIIPMR and QRPMS) concludes the execution of Phase 3 in the case study. The following sections systematically address the case study objectives listed in Table 4.1 in agreement with the above stated.